№ 160(6), June, 2020
Public date: 30.06.2020
Archive of journal: Articles count 15, 43 kb
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TO THE 100TH ANNIVERSARY OF N. I. VAVILOV’S RULE ON HOMOLOGICAL SERIES IN HEREDITARY VARIABILITY
06.01.05 Selection and seed production of agricultural plants (agricultural sciences)
Description100 years ago, on June 4, 1920, 32-year-old Professor of the Saratov University Nikolai Ivanovich Vavilov (1887-1943) first reported at the III all-Russian selection Congress at the University of Saratov on his discovery of homological series in the study of parallelisms in the phenomena of hereditary variability by analogy with homological series of organic compounds. This discovery in genetics received the rank of law, the only one after the laws of G. Mendel. This major study was a further development of the genetic idea of C. Darwin on the origin of species. It showed the ways in which close species and genera of plants have a parallel formative process, because the crucial in the process of evolutionary development of living organisms – first of all, their genetic features. In cases where the development of a trait requires the joint and consistent action of many genes, the occurrence of homological series is inevitable, and this does not contradict the random variability of C. Darwin. In addition to its great genetic significance as a law of evolution, the law of homological series in hereditary variability is of great importance for botanists, plant breeders and breeders: it not only determines the place of each form in the plant world, but can also indicate to the breeder possible directions in his practical work. According to a number of geneticists and breeders, if G. Mendel discovered the rules of heredity, then N. I. Vavilov discovered the rules of variability
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05.20.01 Technologies and means of mechanization of agriculture (technical sciences)
DescriptionThe urgent task facing the agro-industrial complex is the improvement of storage methods for agricultural products and the development of new ones. One of the actively cultivated crops, characterized by a variety of species, valuable taste and medicinal properties – grape. It is possible to provide the population with fresh grapes of high quality through the introduction of effective storage technologies that reduce losses, preserve marketable properties and biological value. One of the effective ways to preserve the quality of grapes during storage is the use of sulfur dioxide (SO2). This gas inhibits oxidative enzymes in berries, thereby reducing the rate of development of the phytopathogen Botrýtis cinérea, which causes gray rot. At the same time, it is especially important to control the rate of release of sulfur dioxide, since at the beginning of storage it is necessary to ensure the receipt of a large amount of it, which will eliminate Botrytis spores present on the surface of the berries and stabilize the existing damage. Further, during the entire period of storage of grapes, sulfur dioxide must be supplied in minimal quantities. Such dynamics of SO2 emission can be ensured by the use of two-phase generators of sulfur dioxide. The article investigated the effects of sulfur dioxide generators on the quality of grapes during storage. The study also investigates quality indicators of grapes of several varieties zoned in the Krasnodar region under long-term storage
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Description
Protection of farm animals from diseases remains one of the priority tasks for veterinary practice. A healthy animal is the key to obtaining high sanitary quality of livestock products. Among the veterinary-sanitary and organizational-economic measures carried out for the prevention and control of infectious diseases, disinfection is of particular importance. In the laboratory of veterinary and sanitary expertise of VNIIVSGE-branch of the Federal State Budget Scientific Institution Federal Research Center of the Russian Academy of Medical Sciences, a new composite preparation “Hyponatum BPO” has been developed and is being tested. The studies found that the "Hyponat BPO" has a high disinfecting effect against gram-positive and gram-negative vegetative microflora, located on surfaces of various materials (wood, concrete, tile, stainless steel, plastic), both with the presence of protein protection, and without it
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06.01.01 General agriculture, crop production (agricultural sciences)
DescriptionThe work shows the effect of the Regalis preparation on the formation and biochemical composition of organs of apple tree plants (using the Gala variety as an example). Experiments were carried out in 2016-2019. Field experiments were carried out in JSC company "Agrocomplex" named after N.I. Tkachev in the Vyselkovsky district. Planting bookmark - 2007. Tree planting scheme 4.0 × 1.0 m., Irrigation - drip. The soil of the study area is ordinary chernozem (carbonate). It was found that under the action of treatments with the Regalis preparation significant changes are recorded in the structure of fouling wood and the area of the sheet apparatus. The use of a growth regulator helps to accelerate the completion of tree growth processes. This is evidenced by a decrease in the content of IAA in the tops of shoots, by 12% in comparison with the control. The “Regalis” had a significant impact on ensuring the stable fruiting of plants of the Gala apple tree. The annual one-three-time treatment of trees with this preparation in a dose of 1.25 kg / ha provided a stable increase in yield to 14.2-16.3 kg from one tree. Moreover, on average for four years, the best results were recorded in the variant with 2-fold treatment with Regalis (16.3 kg-tree). Further analysis of the yield and commercial qualities of the obtained fruits showed that two and three-fold processing contributed to the production of fruits from 38.5 to 40.8 t / ha, which is 10-11.7 t higher than the control, while increasing the yield of marketable fruits up to 13.3 - 14.0 tons
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PROBABILITY-STATISTICAL MODELS OF CORRELATION AND REGRESSION
08.00.13 Mathematical and instrumental methods of Economics
DescriptionThe correlation and determination coefficients are widely used in statistical data analysis. According to measurement theory, Pearson's linear paired correlation coefficient is applicable to variables measured on an interval scale. It cannot be used in the analysis of ordinal data. The nonparametric Spearman and Kendall rank coefficients estimate the relationship of ordinal variables. The critical value when testing the significance of the difference of the correlation coefficient from 0 depends on the sample size. Therefore, using the Chaddock Scale is incorrect. When using a passive experiment, the correlation coefficients are reasonably used for prediction, but not for control. To obtain probabilistic-statistical models intended for control, an active experiment is required. The effect of outliers on the Pearson correlation coefficient is very large. With an increase in the number of analyzed sets of predictors, the maximum of the corresponding correlation coefficients — indicators of approximation quality noticeably increases (the effect of “inflation” of the correlation coefficient). Four main regression analysis models are considered. Models of the least squares method with a determinate independent variable are distinguished. The distribution of deviations is arbitrary, however, to obtain the limit distributions of parameter estimates and regression dependences, we assume that the conditions of the central limit theorem are satisfied. The second type of model is based on a sample of random vectors. The dependence is nonparametric, the distribution of the two-dimensional vector is arbitrary. The estimation of the variance of an independent variable can be discussed only in the model based on a sample of random vectors, as well as the determination coefficient as a quality criterion for the model. Time series smoothing is discussed. Methods of restoring dependencies in spaces of a general nature are considered. It is shown that the limiting distribution of the natural estimate of the dimensionality of the model is geometric, and the construction of an informative subset of features encounters the effect of "inflation coefficient correlation". Various approaches to the regression analysis of interval data are discussed. Analysis of the variety of regression analysis models leads to the conclusion that there is no single “standard model”